物流车辆路径选择中的交通状态预测方法研究

Research on Traffic Condition Forecasting in Logistics Vehicle Routing Problem

以道路服务水平作为反映交通状态的效率指标,通过大量的交通历史数据分析,研究了交通状态预测分模态的ARIMA模型,并进行了实验分析。实验结果表明,该模型能够准确的预测交通状态,并为优化配置物流车辆的路径选择提供有益的参考。

Taking road service level as the efficiency index reflecting traffic conditions, the paper designs a multi-mode ARIMA model of traffic condition forecasting and analyzes it in an experiment. The results show that the model can accurately forecast traffic conditions and provide helpful reference for the optimization of logistics vehicle route selection.